Bibliographic record
Abstract
Feruvite occurs in the Ca-rich exocontacts of lepidolite-subtype granitic pegmatites in the Red Cross Lake pegmatite field, northeastern Manitoba. The pegmatites intrude meta-andesitic to metabasaltic host-rocks.ln addition to tourmaline, exocontacts contain Cs- and Rb-rich biotite, Fe-rich muscovite, epidote, apatite, Ca-rich garnet, titanite, calcite, quartz and arsenopyrite. The tourmaline is commonly zoned, with a core of feruvite surrounded by schorl or dravite, and rimmed by uvite. The most extreme composition of feruvite analyzed is (Ca0_56Na0_39)l:0.95 (Fe2•�.9oMg0_8 1Li0_18Ti0_04Mn0 01));3_00(Al,_31Mgo_69)l:6.oo(BO,),Si6.o70rs [(OH3 51)F0_49]);4_00; the X, Y, and Z sites are dominated by Ca, Fe and AI, respectively. Magnesium is a significant component at the Y and Z sites. In plane-polarized light, uvite and dravite are mainly pale blue or blue, and feruvite and schorl are mainly dark blue. Brown schorl and feruvite tend to be rich inTi. The meta-andesitic and metabasaltic wallrocks provided the Fe and Ca for contact-metasomatic reactions between the wallrocks and the intruding pegmatite to produce feruvite.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.536 | 0.334 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".